Publication: Dynamically driven correlations in elastic net models reveal sequence of events and causality in proteins
Program
KU-Authors
KU Authors
Co-Authors
Erkip Albert
Advisor
Publication Date
2024
Language
en
Type
Journal article
Journal Title
Journal ISSN
Volume Title
Abstract
An explicit analytic solution is given for the Langevin equation applied to the Gauss-ian Network Model of a protein subjected to both a random and a deterministic peri-odic force. Synchronous and asynchronous components of time correlation functionsare derived and an expression for phase differences in the time correlations of resi-due pairs is obtained. The synchronous component enables the determination ofdynamic communities within the protein structure. The asynchronous componentreveals causality, where the time correlation function between residues i and j differsdepending on whether i is observed before j or vice versa, resulting in directionalinformation flow. Driver and driven residues in the allosteric process of cyclophilin Aand human NAD-dependent isocitrate dehydrogenase are determined by a perturba-tion-scanning technique. Factors affecting phase differences between fluctuations ofresidues, such as network topology, connectivity, and residue centrality, are identi-fied. Within the constraints of the isotropic Gaussian Network Model, our resultsshow that asynchronicity increases with viscosity and distance between residues,decreases with increasing connectivity, and decreases with increasing levels of eigen-vector centrality.
Description
Source:
Proteins: Structure, Function and Bioinformatics
Publisher:
John Wiley and Sons Inc
Keywords:
Subject
Dynamics, Protein conformation, Amino acids